【发布时间】:2013-11-22 13:14:53
【问题描述】:
我正在使用 Gabor 过滤器代码,一切似乎都运行良好,但输出图像有问题。
我使用的代码来自这里:Gabor Filters
我创建了 [4x8] 滤光片,它有 8 个方向,每个方向都有不同的波长。
现在我提供了一张图片作为输入:
所以我得到的输出为:
我不应该在黑白中获得一些图像吗?
我的意思是为什么它是彩色的。
当我使用ndims(imgS) 检查尺寸时,它告诉我图像是二维的。
为了清楚起见,这里是 Image 与上述补丁卷积的代码。:
function [img]=Convolve_Gabor(R,C,GW,img)
%if not grayscaled then grayscale it
if ndims(img)>2
img=rgb2gray(img);
end
%Convert to Double so that its accepteble everywhere
img=im2double(img);
% Store the original size.
[m,n] = size(img);
%{
The minimum amount of padding is just "one side" of the filter.
We add 1 if the image size is odd.
assuming the filter size is odd.
%}
pR = (R-1)/2; % make pR half of R
pC = (C-1)/2; % make pC half of C
if rem(m,2) ~= 0; pR = pR + 1; end; % if image height is odd make pR even
if rem(n,2) ~= 0; pC = pC + 1; end; % if image width is odd make pC even
img = padarray(img,[pR pC],'pre'); % Pad image to handle circular convolution.
% Pad all the filters to size of padded image.
% We made sure padsize will only be even, so we can divide by 2.
padsize = size(img) - [R C];
GW = cellfun( @(x) padarray(x,padsize/2),GW,'UniformOutput',false);
imgFFT = fft2(img); % Pre-calculate image FFT.
imgfilt={};
for i=1:length(GW)
filter = fft2( ifftshift( GW{i} ) ); % See Numerical Recipes.
imgfilt{i} = ifft2( imgFFT .* filter ); % Apply Convolution Theorem.
end
%# Sum the responses to each filter. Do it in the above loop to save some space.
imgS = zeros(m,n);
for i=1:length(imgfilt)
imgS = imgS + imgfilt{i}(pR+1:end,pC+1:end); % Just use the valid part.
end
disp(ndims(imgS));
figure,imagesc(abs(imgS)),hold on;
【问题讨论】:
标签: image matlab image-processing grayscale feature-extraction